General

Column

Target



Qual área de pesquisa é emergente?



Qual pesquisador contratar?



Qual patente comprar?



Growth

Networks

Groups Attributes

Column

Shelf Life



Adicionar uma sentença sobre Shelf Life, para catecterizar a área de pesquisa.



  • Shelf Life
  • 13,516 Registers
  • 12.9% Growth Rate
  • 5.6 Years Doubling Time



  • Scopus
  • 52,000,000 Registers
  • 4.13% Growth Rate
  • 17 Years Doubling Time

Segmented Growth

Groups Growth

Groups Description

g01

Aplicação shiny

g02

quadro limpo

insert text here!

Conclusions

Escrever algum texto para finalizar a análise.

---
title: "A4F - Shelf Life"
output: 
  flexdashboard::flex_dashboard:
    navbar:
      - { title: "Research", href: "http://roneyfraga.com/dash/2020_A4F", align: right }
      - { title: "People", href: "http://roneyfraga.com/dash/2020_A4F/#people", align: right }
      - { title: "Patent", href: "http://roneyfraga.com/dash/2020_A4F/#patent", align: right }
      - { title: "About", href: "http://roneyfraga.com/", align: right }
    social: [ "menu" ]
    source_code: "embed"
    theme: bootstrap #yeti #lumen
    logo: img/logo.png
runtime: shiny
---



```{r setup, include=FALSE}
options(scipen=999)
library(rmarkdown)
library(flexdashboard)
library(pipeR)
library(tidyverse)
library(rio)
library(ggraph)
library(tidygraph)
library(DT)
library(visNetwork)
library(igraph)
library(highcharter)
library(htmlwidgets)
library(printr)
library(shiny)
```

# General 


Column {data-width=500 .tabset}
-------------------------------------


### Target



Qual área de pesquisa é emergente?



Qual pesquisador contratar?



Qual patente comprar?



### Growth ```{r} import('data/growth_shelf_life.rds') %>>% (. -> d2) hchart(d2, "column", hcaes(x = Year, y = Publications), name = "Publications", showInLegend = TRUE) %>>% hc_add_series(d2, "line", hcaes(x = Year, y = predicted), name = "Predicted", showInLegend = TRUE) %>>% hc_add_theme(hc_theme_elementary()) %>>% hc_navigator( enabled = TRUE) %>>% hc_exporting( enabled = TRUE, filename='groups_growth') ``` ### Networks ```{r} import('data/networks.rds') %>>% (~ .$nodes -> nodes) %>>% (.$edges -> edges) visNetwork(nodes, edges, height = "700px", width = "100%", main = as.character(max(nodes$PY))) %>% visNodes(size = 10, shape='dot') %>>% visEdges(width = 2, hidden=F) %>>% visOptions(selectedBy = "group", highlightNearest = TRUE, nodesIdSelection = F) %>>% visPhysics(stabilization = T) %>>% visGroups(groupname = "g01", color = "#38501e") %>>% visGroups(groupname = "g02", color = "#23331e") %>>% visGroups(groupname = "g03", color = "#6e1d21") %>>% visGroups(groupname = "g04", color = "#472926") %>>% visGroups(groupname = "g05", color = "#926433") %>>% visGroups(groupname = "g06", color = "#a90a26") %>>% visGroups(groupname = "g07", color = "#97863e") %>>% visGroups(groupname = "g08", color = "#00FFFF") %>>% visGroups(groupname = "g09", color = "#d48d01") %>>% visGroups(groupname = "g10", color = "#021338") %>>% visGroups(groupname = "g11", color = "#e6d82e") %>>% visGroups(groupname = "g12", color = "#9eb739") %>>% visGroups(groupname = "g13", color = "#808080") ``` ### Groups Attributes ```{r} import('data/groups_attributes.rds') %>>% datatable(extensions = 'Buttons', options = list( dom = 'Bfrtip', buttons = list(list( extend='collection', buttons = list(list(extend='csv',filename='data'), list(extend='excel',filename='data')), text='Download')))) %>>% formatRound('GrowthRateYear',1) ``` Column {data-width=500 .tabset} ------------------------------------- ### Shelf Life

Adicionar uma sentença sobre Shelf Life, para catecterizar a área de pesquisa.



> - __Shelf Life__ > - 13,516 Registers \n > - 12.9% Growth Rate \n > - 5.6 Years Doubling Time \n

> - __Scopus__ > - 52,000,000 Registers \n > - 4.13% Growth Rate \n > - 17 Years Doubling Time \n > ### Segmented Growth ```{r, out.width='75%'} import('data/segmented_growth.rds') %>>% (. -> d2) hchart(d2, "line", hcaes(x = Year, y = ln_Publications), name = "Publications", showInLegend = TRUE, fillOpacity = 0.2) %>>% hc_add_series(d2, "line", hcaes(x = Year, y = est), name = "Segmented Regression", showInLegend = TRUE, fillOpacity = 0.2) %>>% hc_add_theme(hc_theme_elementary()) %>>% hc_navigator( enabled = TRUE) %>>% hc_exporting( enabled = TRUE, filename='segmented_growth') %>>% hc_xAxis( plotBands = list( list( from = 1986, to = 1986, color = "#330000" ), list( from = 1992, to = 1992, color = "#330000" ), list( from = 2004, to = 2004, color = "#330000" ) )) ``` ### Groups Growth ```{r} import('data/groups_growth.rds') %>>% (. -> groups_growth) hchart(groups_growth, "line", hcaes(x = Year, y = Publications, group = Group), fillOpacity = 0.2) %>>% hc_add_theme(hc_theme_elementary()) %>>% hc_navigator( enabled = TRUE) %>>% hc_exporting( enabled = TRUE, filename='groups_growth') ``` ### Groups Description ```{r} data.frame(Group=paste0('g',1:13),Description='algum texto para descrever o grupo') %>>% datatable(extensions = 'Buttons', options = list( dom = 'Bfrtip', buttons = list(list( extend='collection', buttons = list(list(extend='csv',filename='data'), list(extend='excel',filename='data')), text='Download')))) ``` # g01 {data-navmenu="Groups"} ### Aplicação `shiny` ```{r echo=F, eval=T} numericInput("obs", label = "Number of carbs:", 2, min=1, max=8) show_mtcars <- reactive({ mtcars %>>% dplyr::filter(carb == input$obs) }) renderTable(show_mtcars()) ``` # g02 {data-navmenu="Groups"} ### quadro limpo > insert text here! # Conclusions Escrever algum texto para finalizar a análise. # People {.hidden} Adicionar os grandes números do Lattes. # Patent {.hidden} Em construção.